Active Listening and AI Part 2

 This article is a continuance of Active listening Part 1, and how it will interface with AI. As the reader, you are interested in how AI will benefit, change, and/or disrupt your own personal world.

In many ways, there will be huge improvements to simply your life, as artificial intelligence WILL streamline many fields of endeavor to eliminate both small and consummate errors.

AI will rule data management, much to the relief of business and industry. Heath Care management will greatly benefit. Case in point: In the following incidence, I would have been grateful for an AI intervention like data management.

Recently, I endured a series of catapulting errors trying to get and prescription order filled. I finally did, but it took nearly a week of vacillating communication issues between the nurse, pharmacist, and me. 

Once an initial set of data was submitted, the pharmacist found another detail gap. 

The order remained in abstract limbo. It took my time and energy to finalize the order.  Humans have to organize information and notice discrepencies.

It had become chaotic mis-management. AI will streamline these routine data entries, and can offer additional competence, but, AI will NOT be able to THINK for the prescribing nurse. or the pharmacist, who is processing a specific order, having detailed instructions. It requires cognitive integration, of which listening is an integral component.

This type of personal hassle, you the reader, can relate to this. Similar incidences become daily nightmares to cope with. Life soon becomes too complicated.

Subsequently and conversely, AI will not manage human thought processes involving logical problem solving or unique innovations. Many life decisions will require your own, awareness and ability to resolve the problem. You wind up regretting having made unwise decisions and bad choices.  

Your life soon becomes chaos.

However, you can seek your own solutions. However, this requires enough memory strength to compare multiple options.

Answer lies in increasing our Critical Thinking Processes

How do we accomplish this achievement?

In review, active listening is the ability to integrate enough info correctly through cognitive integration, to make decisive judgments that benefit us. (see Hierarchy of Thinking model). The first step is to improve your own listening ability and memory levels to increase your self- awareness and monitoring.

Critical Thinking can only be achieved through deep learning rehearsal practice, and not though medications and pills, which might clear brain fog, but do not generate cohesive thought.

Bottom line: Training is a gradual, incremental process, like learning to play the a musical instrument or playing an athletic game.  Expertise does not happen overnight.  But, your gradual road toward excellence may be your feeling of accomplishment and resilient well-being.

Erland, J. K.  (1989c, 1980). The Hierarchy of Thinking Model.  Lawrence, KS. online; Academia.edu (2024). Jan Kuyper Erland.

Your Active Listening Capability vs. AI

Will Artificial Intelligence replace active listening and inter-communication?

This article series, as an early pioneer in cognitive neuroscience, as a lay practioner, can give you, the reader, hopeful communicative insight. We can find much discourse on this topic on social media. 

There are many viewpoints to consider.

My earlier article on “Listening Success” (February 18, 2024), outlined three types of listening; passive, active, and critical. 

That being said, can Artificial Intelligence replace active and critical listening, crucial components of inter-personal communicative skills and interaction?

The answer is a resounding “no.”  Why, so?

Business, educational, medical, and technical positions will always depend upon personal interaction with feelings and intent.

 AI cannot copy this.

There will also be conferencing and working in teams that will require inter-active communication. Subsequently, inter-personal thought patterns will be outside of AI.

Active listening requires cognition. Without it, you are relegated to only visual memory and careers that utilize the visual process.

Example: Lawn businesses and factory line work require only minimal critical- active, listening. It is primarily visual work.

     i.e. I live on a street where every house employs a difference lawn landscaping company, as there are multitudes to choose from.  

The owner often entails the workload personally, as his lawn assistants cannot follow the necessary, mandatory, oral directions. (auditory memory).

To compound the situation, the lawn proprietor also has limited sequential, listening memory.

Out hiking, I noticed a homeowner giving a lawn proprietor detailed instruction. The latter looked overly confused, as he could not follow, or remember, the procedural instructions entailed.

Subsequently, the specifics were accidentally skipped. Later, the disgruntled home owner then hired another company with the same problem.

Unfortunately, the town is saturated with lawn companies. It is an easy business to acquire the necessary equipment, as failed lawn services soon go broke, (after two or three years in the red), and sell their equipment at a loss to another aspiring lawn company.

Perhaps, it would be better to acquire active listening memory ability; even if it requires some effort. For enhanced performance, The Bridge to Achievement program requires deep learning practice like athletic and musical performance.

                

t may be time to lessen time spent on visual video games, and consider listening development.

 

 

AI and the Human Mind: Our Third Brain?

AI and the Human Mind: Our Third Brain? [1]

 By Jan Kuyper Erland

 

Recently, having completed my 5-generational researched and developed puppetry film project, it is prudent to discuss the threat of Artificial Intelligence (AI) and how it might mimic The Bridge to Achievement’s (BTA) layered components effectively.

The Irony of The Bridge to Achievement’s lengthy project: How AI mechanical images and sound may affect any completed project output in unknown objectionable ways, yet could have assisted greatly with the long, arduous writing and procedural details process. [2]

Comparing our own vocal/musical sounds compared with Open AI mechanical sounds

 The mechanical written sentences and vocals can be easily captured through ChatGPT. Pitch, rhythm, and pace could be copied easily by AI; but intonation and emotional expression is questionable. Attitudes may be hidden.

Subsequently, unique talent can become difficult to imitate fully. The inner personality is not like the original spirit. Specialized talent’s feelings and nuances become  difficult to convey mechanically.

Spoken and musical phrasing is unique to the speaker’s voice. It can be interpreted a special way according to the mental rhythm of the intoned speech. Two singer’s or actor’s voices may replicate sound through AI similarly, but the replication would not create the same layered tonal quality, sensation, through emotional, meaningful intent.

 AI versus Human Language Considerations

For example, prosody and phonological awareness has adapted mechanical sound variations by Siri chat and in various listening pathology treatments for simple, direct communicative value. Yet, the BTA offers multiple, complex, dramatic looping variations for upskilling capabilities uniquely and artistically. 

 AI Written Work Productivity

CEOs are bombarded with tech app requests to streamline written work procedures and project demands with AI. Unfortunately, there are multiple constraints: algorithms take time to develop, are costly to build as each factor has variables. To complicate the situation, there are few data scientists available to fill the roles, let alone convey reasonable expectations and outcomes.

That being said, how will the written sentence convey consistent, intended messaging with logic and reasoning?  Unfortunately, ChatGBT platforms can convey misinformation leading to a myriad of personal and legal entanglements. This aspect will be determined in written evaluative discourse within future data outcomes.

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[1]  Hao, J, Cutter, C., and Morenne, B, (February 20, 2023). From CEOs to Coders, Employees Experiment with New AI Programs. New York, NY, The Wall Street Journal. TECH. pp.1-7.

[2] Erland, J. K. (© 2008). Downloadable, unpublished report. Five Generations, 27-years of iterative Brain-Based Accelerative Learning Experimentation Demonstrate Cognitive Skill Improvement Enhances Academic and Career Goals. (https://memspan/jalt).